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So I’m listening to this audiobook called “Range” and it has an interesting case about how students were given a case study and they based their conclusions without asking for more data from the prof. What’s shocking is that it was modeled after a true case of NASA’s 1986 Challenger shuttle explosion. Below is a very helpful notes summary from a website post with the link here
” Chapter 11: Learning to Drop Your Familiar Tools
- Story about the Carter Racing case study used in MBA programs. A team of students must determine whether or not the Carter Racing team’s car should compete in the biggest race of the season. The team is given data about previous engine failures and the ambient temperature at race-time on those days. After making a decision, the teams are given missing data which nobody thought to ask for. Once the missing data is furnished, it becomes clear that engine failure occurs in every race below 65F.
- The Carter Racing case study is based on NASA’s 1986 Challenger shuttle explosion. The Challenger disaster exhibited the same phenomenon: nobody thought to look at data points where there were NO problems. [me: very similar to Wald’s bullet holes in WW2].
- “We often just use the data people put in front of us…we don’t do a good job of saying, ‘Is this the data that we want to make the decision we need to make?’”
- The Carter Racing case study is a “stark lesson in the danger of reaching conclusions from incomplete data, and the folly of relying only on what is in front of you.”
- Challenger disaster goes further than just being about missing data. “NASA’s real mistake was to rely on quantitative analysis too much.””
Ironically a few hours later something came up at work, everyone needing to make a decision for case X but it was not clear which option is better. Then I remembered that case study and reached out to another team for more info, guess what? turns out they do have more info, that turned out to be helpful.
It sounds so simple, but I can already recall a few times when asking for more data would’ve saved time and effort of multiple teams rather than trying out multiple solutions as the better one wasn’t clear.
When in time crunch to make a decision, we need to try to remember and ask ourselves and involved teams “is there more or different data that can help us make this decision?”
What’s a time more data helped you out? Let us know in the comments!
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Disclaimer: None of this information is to be used as advice, it’s just for entertainment purposes. Additionally, all information used is publicly available.
References:
Range book notes: https://mentalpivot.com/book-notes-range-by-david-epstein/
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